Detecting student frustration based on handwriting behavior

Hiroki Asai, Hayato Yamana

研究成果: Conference contribution

7 被引用数 (Scopus)

抄録

Detecting states of frustration among students engaged in learning activities is critical to the success of teaching assistance tools. We examine the relationship between a student's pen activity and his/her state of frustration while solving handwritten problems. Based on a user study involving mathematics problems, we found that our detection method was able to detect student frustration with a precision of 87% and a recall of 90%. We also identified several particularly discriminative features, including writing stroke number, erased stroke number, pen activity time, and air stroke speed.

本文言語English
ホスト出版物のタイトルUIST 2013 Adjunct - Adjunct Publication of the 26th Annual ACM Symposium on User Interface Software and Technology
ページ77-78
ページ数2
DOI
出版ステータスPublished - 2013 11 15
イベント26th Annual ACM Symposium on User Interface Software and Technology, UIST 2013 - St. Andrews, United Kingdom
継続期間: 2013 10 82013 10 11

出版物シリーズ

名前UIST 2013 Adjunct - Adjunct Publication of the 26th Annual ACM Symposium on User Interface Software and Technology

Conference

Conference26th Annual ACM Symposium on User Interface Software and Technology, UIST 2013
CountryUnited Kingdom
CitySt. Andrews
Period13/10/813/10/11

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Software

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